*4.1. Input*

The proposed deep model has double-channel inputs: raw sample *x*(*t*) from the input matrix and six statistic components *Statistics*(*x*(*t*)), which can be written as:

$$\text{In} = \{ (\mathbf{x}(t), \text{ Statistics}(\mathbf{x}(t))) \} \tag{19}$$

Moreover, we transform the raw sample into one tensor with the shape of (24, 1), and six tuples *Stati*stics into tensor with the shape of (6, 1) to satisfy the input requirements of the deep model. The reshaped tensor is defined in (20).

$$Tensor\_{\rm in} = \{ \text{Reshape}(\text{In}) \} = \{ (\text{Reshape}(\text{x}(t)), \text{Reshape}(\text{Statistic}(\text{x}(t)))) \} \tag{20}$$
